The original idea for the codegen preprocessor was to perform init & prepare stages using a simulator and capture the output. This idea is being abandoned in favor of generating the necessary structures from python.
BUG=cleanup
As the next step in the codegen experiment, we want to generate the invoke calls for each layer. This is slightly challenging with the existing sources, as kernels only expose a registration function, not their individual Eval functions. In an effort to keep the code churn to a minimum, this PR introduces an inference only registration structure and function. It includes just two function pointers: invoke and reset. For this CL, we've only introduced it for FullyConnected.
In the code generator, this PR creates a new op_table array in the generated source, with an enum for lookup. It also generates an invoke function for each subgraph, that calls each operator's invoke function.
BUG=295174388
This PR creates the initial code generator scaffolding for performing inference without an interpreter. Currently, this does nothing other create a header and source file from Mako templates. Mako was chosen as a template engine due to existing dependency.
BUG=b/295076487
